Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add rampstackco/claude-skills --skill pm-spec-writinggit clone --depth 1 https://github.com/rampstackco/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/rampstackco/claude-skills/pm-spec-writing)<a href="https://agentmods.dev/skills/rampstackco/claude-skills/pm-spec-writing"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/pm-spec-writing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/rampstackco/claude-skills/pm-spec-writing"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/pm-spec-writing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00137 | $0.02068 |
| Opus 5 | $0.00068 | $0.01034 |
| Sonnet 5 | $0.00027 | $0.00414 |
| Haiku 4.5 | $0.00014 | $0.00207 |
Grade A, and why
pm-spec-writing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- pm-spec-writing — 94% identical, 6 lines differ
- pm-spec-writing — 94% identical, 6 lines differ
How it starts
The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM Spec Writing
Take an idea (often vague) and turn it into a specification a developer or AI agent can actually build from. Stack-agnostic. Works for new features, bug fixes, content changes, or infrastructure work.
When to use
- Translating an idea into a buildable feature spec
- Writing a PRD or product requirement document
- Filing a bug report that someone else can act on
- Scoping a project before kickoff
- Prioritizing a backlog of feature requests
- Writing acceptance criteria for an existing feature
- Breaking a large initiative into shippable increments
When NOT to use
- Quarterly or annual planning across multiple initiatives (use
roadmap-planning) - Code review or debugging existing code (use
code-review-web) - Design decisions for a feature already specced (use
design-standards) - User research to validate an idea (use
ux-research)
Required inputs
- The idea, request, or problem being addressed
- The audience or user affected
- Any existing constraints (stack, deadlines, dependencies)
- The success metric (how will you know it worked?)
If the idea is vague, the workflow's first step is clarification. Do not write specs around vagueness.
The framework: 4 phases
Every PM workflow follows the same arc. The phases are universal even if the specific outputs vary.
Phase 1: Clarify the idea
Before any spec, answer four questions. If any answer is "I don't know," go back to the user.
- What user problem does this solve? Not "what does it do." The problem comes first; the feature is the proposed solution.
- Who specifically benefits? Be precise. "Users" is not specific. "First-time visitors who don't convert" is.
- What is the success metric? How will you know it worked? Pick one primary metric.
- Why now? What changed that makes this the right time to build it? If "nothing changed," it might not be the right time.
Phase 2: Scope by impact and effort
Plot every candidate idea on the impact/effort grid:
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 233 lines · 137 tokens per session scan A 17c08255d5ba
pm-spec-writing is a skill published in the GitHub repository rampstackco/claude-skills (832 stars, last pushed 2d ago), licensed MIT. It adds 137 tokens to every session and 2,068 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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